| Title |
Temperature and rainfall are related to fertility rate after spring artificial insemination in small ruminants
|
|---|---|
| Published in |
International Journal of Biometeorology, March 2016
|
| DOI | 10.1007/s00484-016-1150-y |
| Pubmed ID | |
| Authors |
J. A. Abecia, F. Arrébola, A. Macías, A. Laviña, O. González-Casquet, F. Benítez, C. Palacios |
| Abstract |
A total number of 1092 artificial inseminations (AIs) performed from March to May were documented over four consecutive years on 10 Payoya goat farms (36° N) and 19,392 AIs on 102 Rasa Aragonesa sheep farms (41° N) over 10 years. Mean, maximum, and minimum ambient temperatures, mean relative humidity, mean solar radiation, and total rainfall on each insemination day were recorded. Overall, fertility rates were 58 % in goats and 45 % in sheep. The fertility rates of the highest and lowest deciles of each of the meteorological variables indicated that temperature and rainfall had a significant effect on fertility in goats. Specifically, inseminations that were performed when mean (68 %), maximum (68 %), and minimum (66 %) temperatures were in the highest decile, and rainfall was in the lowest decile (59 %), had a significantly (P < 0.0001) higher proportion of does that became pregnant than did the ewes in the lowest decile (56, 54, 58, and 49 %, respectively). In sheep, the fertility rates of the highest decile of mean (62 %), maximum (62 %), and minimum (52 %) temperature, RH (52 %), THI (53 %), and rainfall (45 %) were significantly higher (P < 0.0001) than were the fertility rates among ewes in the lowest decile (46, 45, 45, 45, 46, and 43 %, respectively). In conclusion, weather was related to fertility in small ruminants after AI in spring. It remains to be determined whether scheduling the dates of insemination based on forecasted temperatures can improve the success of AI in goats and sheep. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 5% |
| Unknown | 21 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 18% |
| Student > Doctoral Student | 3 | 14% |
| Researcher | 3 | 14% |
| Professor | 3 | 14% |
| Other | 2 | 9% |
| Other | 3 | 14% |
| Unknown | 4 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 36% |
| Veterinary Science and Veterinary Medicine | 4 | 18% |
| Computer Science | 2 | 9% |
| Medicine and Dentistry | 1 | 5% |
| Unknown | 7 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 March 2016.
All research outputs
#20,315,221
of 22,856,968 outputs
Outputs from International Journal of Biometeorology
#1,189
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#252,368
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Outputs of similar age from International Journal of Biometeorology
#16
of 21 outputs
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